利用径向速度观测值提高目标跟踪性能

提出了在三维空间中引入径向速度的非线性卡尔曼滤波算法．先将观测数据从三维极坐标转换成直角坐标，然后将径向速度和状态变量之间的非线性方程在预测值处利用泰勒级数展开，得到其一阶近似的线性方程，最后用标准卡尔曼滤波算法进行滤波．仿真结果表明，当引入径向速度时，相对于只有目标的位置观测来说其收敛速度加快，均方误差减小，提高了跟踪性能．

The use of the radial velocity to improve the performance of target tracking

Based on three-dimensional space, a new method for the nonlinear Kalman filter using the radial velocity is presented. The polar coordinates which where observed are converted to the rectilinear coordinates first. Then the nonlinear function of the radial velocity is expanded in a Taylor series around the predicted state estimate. So the standard Kalman filter can be used. Simulation results show that the evaluated error is decreased and the convergent velocity is accelerated when the radial velocity is introduced.